Siting assessment for CO2 sequestration in depleted gas reservoirs based on multilevel fuzzy evaluation method: From field screening to mechanistic modeling

Geological carbon storage (GCS) is an essential technology for mitigating greenhouse gas emissions and achieving carbon neutrality. However, selecting available storage sites remains challenging due to uncertainties within a hierarchical network of geological and engineering parameters. This study proposes an integrated assessment model combining the analytic hierarchy process (AHP) with multilevel fuzzy comprehensive evaluation (MFCE). The tailored framework employs bottom-up aggregation for multi-criteria decision-making in site selection, and adopts a sinusoidal membership function to characterize the ambiguous fuzzy boundaries. The workflow involves indicator screening, comparison, quantification, and ranking. The proposed AHP-MFCE model is applied to six blocks in the Sichuan Basin, with modeling practice for the target site. A comprehensive indicator system is established, comprising 33 sub-indicators across four categories: reservoir, caprock, well, and surface conditions. After passing the consistency check (CR = 0.0006 < 0.1), the category weights are determined as 0.3991, 0.2740, 0.1938, and 0.1330, respectively. Sub-indicators with composite weights exceeding 0.02 should be prioritized to reduce subjective impacts and enhance the objectivity of the evaluation results. Field studies indicate that Blocks #E and #D are identified as potential GCS candidates. Blocks #A, #B, and #C are rated as average, while Block #F is classified as fair. Numerical simulation coupled with geochemical reactions for Block #E confirms its considerable storage capacity and injectivity. The findings support site selection for pilot-scale GCS projects in depleted gas reservoirs and contribute to long-term storage safety and leakage risk mitigation.